The closest OpenClaw alternative in 2026 is Hermes Agent: the same "agent in your messenger" idea, MIT licence, Telegram, Discord, Slack, WhatsApp and Signal, a terminal tool with Docker and SSH backends, and MCP support. Open WebUI, LibreChat and AnythingLLM are mature self-hosted chat platforms with agents and MCP but no messenger bot, while n8n and Dify are workflow builders that suit multi-step business automations better than a personal assistant. This comparison uses only facts from each project's own repository or documentation, checked on 14 September 2026.
What you are replacing: OpenClaw in short
OpenClaw is an MIT-licensed personal AI agent from the OpenClaw Foundation (github.com/openclaw/openclaw). One long-lived process, the Gateway, owns every messaging surface (Telegram and WebChat ship with the core install; Discord, Slack, Signal, WhatsApp, iMessage, Matrix, Microsoft Teams and many more are official plugins, installed during onboarding or with openclaw plugins install), talks to Anthropic, OpenAI, Google, Ollama, llama.cpp, LM Studio, vLLM or any OpenAI-compatible endpoint, and gives the model tools: exec (a shell), browser automation, web search, cron jobs, skills and MCP servers declared under mcp.servers. The Gateway binds to 127.0.0.1:18789 by default and an unknown DM sender gets a pairing code, which you approve with openclaw pairing approve <channel> <code>.
curl -fsSL https://openclaw.ai/install.sh | bash
# or: npm install -g openclaw@latest --allow-scripts=openclaw
openclaw onboard --install-daemonNode 24.16+ or 26.1+ is required; Docker images are ghcr.io/openclaw/openclaw:latest and the Chromium-equipped :latest-browser, with state in ~/.openclaw. The newest release listed is v2026.9.4. Sandboxing is off by default; agents.defaults.sandbox.mode turns it on with Docker, Podman, SSH, OpenShell or Crabbox backends. In our deployments (2026.6.1) the "all" mode needed the docker command inside the Gateway container, so we ship sandbox off and lock the bot to its owner through channels.telegram.allowFrom. The product is remote code execution by design: the README says to treat inbound messages as untrusted, and OpenClaw had CVE-2026-25253 (a one-click RCE through token theft) in 2026. Keep port 18789 on loopback behind an SSH tunnel or Tailscale.
Comparison table
| Project | Messaging channels | Tool and shell execution | Sandboxing | Local models | MCP support | Licence | Install effort |
|---|---|---|---|---|---|---|---|
| OpenClaw | Telegram and WebChat in core; WhatsApp, Discord, Slack, Signal, iMessage and more as official plugins | exec shell, browser, web search, cron, skills | Off by default; Docker, Podman, SSH, OpenShell or Crabbox backends | Ollama, llama.cpp, LM Studio, vLLM, any OpenAI-compatible endpoint | Yes, mcp.servers in openclaw.json; stdio, SSE and streamable HTTP | MIT | Low: install script or npm, then onboard |
| Hermes Agent | Telegram, Discord, Slack, WhatsApp, Signal, CLI | Terminal tool with seven backends including local, Docker and SSH | Through the Docker or remote backends; local backend is unconfined | Any endpoint (Nous Portal, OpenRouter, OpenAI, your own) | Yes, any MCP server | MIT | Low: one install script |
| Open WebUI | None in core; a separate Computer companion is reachable from Telegram per the README | Python tools in the chat; Open Terminal add-on runs real commands | Not in core; Open Terminal is a separate environment | Ollama, any OpenAI-compatible API | Yes, MCP, MCPO and OpenAPI tool servers, native Streamable HTTP | Open WebUI License (BSD-3 base, branding clause above 50 users) | Low: a single docker run |
| LibreChat | None | Agents with tools, file search and Code Interpreter | Code runs in a separate self-hosted ClickHouse/code-interpreter service | Ollama and custom OpenAI-compatible endpoints | Yes, MCP servers attached to agents | MIT | Medium: docker compose plus a second service for code |
| AnythingLLM | None | @agent skills (web browsing, files, SQL, scheduled jobs), custom NodeJS skills; no shell tool in the docs | None documented | Ollama, LM Studio, LocalAI, llama.cpp-compatible models | Yes, anythingllm_mcp_servers.json, stdio, SSE, streamable | MIT | Low: docker or desktop app |
| n8n | Telegram Trigger node and other chat integrations as nodes | AI Agent node plus tools; Execute Command runs shell on the n8n host, off by default since 2.0 | None for Execute Command | Ollama Chat Model node, OpenAI-compatible providers | Yes, MCP Client Tool (SSE) and MCP Server Trigger | Sustainable Use License (fair-code, not OSI open source) | Low to medium: docker run, then build the workflow |
| Dify | None in core | Agents (function calling or ReAct), 50+ built-in tools, code node | dify-sandbox service (Apache-2.0, seccomp) | Any OpenAI API-compatible model | Yes, HTTP transport only; apps can be published as MCP servers | Dify Open Source License (Apache 2.0 with conditions) | High: 16 containers, 2 cores and 4 GiB minimum |
Hermes Agent: the only like-for-like alternative
Hermes Agent by Nous Research (github.com/NousResearch/hermes-agent) is the one project here that solves the same problem as OpenClaw: a personal agent you reach from Telegram, Discord, Slack, WhatsApp, Signal or the CLI, with a terminal tool the model can use. Its terminal has seven backends (local, Docker, SSH, Singularity, Modal, Daytona, Vercel Sandbox), so sandboxing works as in OpenClaw: Docker or a remote backend for isolation, local for an unconfined shell. It connects to "any MCP server", and its distinctive feature is a learning loop that creates skills from experience. Models come from Nous Portal, OpenRouter, OpenAI or "your own endpoint". It is MIT-licensed and installs with one script:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bashWe have not run Hermes Agent in production, so we cannot compare its hardening defaults with OpenClaw's pairing flow; read its security section first.
Open WebUI: best chat UI, not a messenger bot
Open WebUI (github.com/open-webui/open-webui) is the most polished self-hosted chat interface for Ollama and OpenAI-compatible providers, with roles, groups and permissions. Tools are Python scripts that run in the chat, plus MCP, MCPO and OpenAPI tool servers. Command execution is not in the core: the README describes Open Terminal as a separate self-hosted environment where the model writes and runs code. Its "Channels" are shared rooms for people and models, not Telegram; the README also mentions a companion, Open WebUI Computer, reachable "from Telegram, WhatsApp, and more", which we have not tested. The licence is BSD-3 with a branding clause: the Open WebUI branding may only be removed at or below 50 end users in any rolling 30 days, or with written permission or an enterprise licence. Install is one command:
docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:mainLibreChat: agents with a real code sandbox, browser only
LibreChat (github.com/danny-avila/LibreChat) is MIT-licensed and ships as compose files (docker-compose.yml for a standard setup, deploy-compose.yml for production). It talks to OpenAI, Anthropic, Google, Ollama and any OpenAI-compatible endpoint. Its Agents feature gives you no-code assistants with MCP servers, tools, file search and code execution. The Code Interpreter matters for anyone leaving OpenClaw over security: code runs in a separate sandboxed service, ClickHouse/code-interpreter (Apache 2.0), which you deploy yourself and reference through LIBRECHAT_CODE_BASEURL; it supports Python, Node.js, Go, Java, PHP, Rust and more. What it lacks is any messenger channel.
AnythingLLM: local-first agents with MCP, no shell
AnythingLLM (github.com/Mintplex-Labs/anything-llm) is MIT-licensed and comes as a desktop app or a Docker image; multi-user support is Docker only. It lists more than 40 providers including Ollama, LM Studio and LocalAI. You start an agent turn by typing @agent; default skills include RAG search, web browsing, save files, SQL agent, file system agent, Gmail, Google Calendar and scheduled jobs, and you can write custom skills in NodeJS (plugin.json plus handler.js) or compose Agent Flows. MCP servers live in anythingllm_mcp_servers.json inside the storage plugins directory, stdio by default, SSE or streamable over a url. Its agent docs describe no shell tool and no sandbox, which makes it the safest platform here and the least OpenClaw-like.
n8n: an agent inside a workflow engine
n8n (github.com/n8n-io/n8n) is fair-code under the Sustainable Use License with a separate Enterprise License, so it is source-available rather than OSI open source. Self-hosting is one container:
docker volume create n8n_data
docker run -it --rm --name n8n -p 5678:5678 -v n8n_data:/home/node/.n8n docker.n8n.io/n8nio/n8nThe AI Agent node takes a chat model (the Ollama Chat Model sub-node covers local models) and at least one tool sub-node; the MCP Client Tool node connects to an MCP server over SSE, and an MCP Server Trigger exposes n8n tools to outside agents. A Telegram Trigger node reacts to bot updates, so Telegram in, agent, reply out is a few nodes. The catch is shell access: the Execute Command node "runs shell commands on the host machine that runs n8n" and is "disabled by default from n8n 2.0" because of the security risk, with no sandbox around it.
Dify: heaviest install, proper code sandbox
Dify (github.com/langgenius/dify) is a full LLM application platform under the Dify Open Source License, Apache 2.0 with additional conditions. The official docker compose up -d brings up 16 containers and the documented minimum is 2 CPU cores and 4 GiB RAM. Agents use function calling or ReAct with 50+ built-in tools, models include any OpenAI API-compatible endpoint, and code nodes run in dify-sandbox, an Apache-2.0 service built on seccomp. MCP works both ways: workspace Tools import an MCP server over HTTP transport only, and an app can be published as an MCP server. There is no messenger channel.
Two candidates we checked and left out
- Botpress. The main repository is MIT but holds tooling for Botpress Cloud; the self-hostable Botpress v12 is dual-licensed under AGPLv3 and a proprietary licence and its README sends you to the Cloud docs. It has Telegram, WhatsApp and Slack channels, but it is a chatbot builder, not a tool-running agent.
- LangGraph. MIT,
pip install -U langgraph, but a low-level orchestration framework for stateful agents: no messenger, sandbox or UI until you write them.
Which one fits which user
- Same thing as OpenClaw, different project: Hermes Agent. Same channels, same shell-plus-MCP model, same duty to sandbox it yourself.
- Private ChatGPT for a team, tools secondary: Open WebUI for roles and the best UI, LibreChat for an isolated code interpreter and an MIT licence with no branding clause.
- Local-model assistant that cannot run a shell: AnythingLLM.
- An automation with an LLM step: n8n, with Execute Command kept off.
- Agent products for others: Dify, if you can afford its stack.
- Staying with OpenClaw: Gateway on loopback, pairing on, browser image only if needed.
All seven run on an ordinary Linux server; a 2 vCPU, 4 GB VPS covers everything except Dify comfortably, and a GPU is needed only when you host the model yourself (see what server to run a local AI model). If you choose the OpenClaw route and would rather skip the Docker, hardening and Telegram wiring, our ready OpenClaw server comes with the Gateway preinstalled on Ubuntu 24.04 from 9.35 EUR per month; you add your model key and bot token.
Questions
Is there an OpenClaw alternative that does not need Docker?
Hermes Agent and OpenClaw both install with a shell script and run without a container; Docker matters only for a sandbox around the terminal tool. AnythingLLM has a desktop app. Open WebUI, LibreChat, n8n and Dify are distributed mainly as Docker images or compose files.
Which alternative is the safest for a beginner?
AnythingLLM, because its documented agent skills do not include a shell. Among the messenger-capable options there is no safe default: OpenClaw and Hermes Agent both hand the model a terminal, so the owner allowlist and a Docker or SSH sandbox are the safety mechanism, not the product.
Can all of them use local models instead of an API?
Yes. OpenClaw, Open WebUI, LibreChat, AnythingLLM and n8n name Ollama directly; Dify and Hermes Agent accept any OpenAI-compatible or custom endpoint, which is how a local runtime is normally exposed. Tool use quality depends on the model, and small local models often ignore tools.
Why is a messenger bot with shell access risky at all?
Because anyone who can message the bot, or steal its session, can run commands on your server. That is why OpenClaw answers unknown senders with a pairing code and binds to loopback. The same applies to Hermes Agent and to any n8n workflow with Execute Command enabled: restrict who can talk to it and what it can reach.